Metabolic processes within a cell produce the energy and small molecule building blocks necessary for all cellular functions, and central carbon metabolism - the key metabolic module governing energy sources - is the cornerstone of these processes. Despite this key role, we understand surprisingly little about the function and evolution of central carbon metabolism on a systems scale. For example, how did the respiro- fermentative metabolic state (common to log-phase Saccharomyces cerevisiae and to many cancer cells) evolve and what are its adaptive advantages? In this project we propose a comparative experimental and computational study of the function, regulation, and evolution of central carbon metabolism in thirteen Ascomycota fungi spanning 300 million years of evolution. Using advanced metabolomics methods, we will systematically measure metabolite concentrations and fluxes under a variety of metabolic and genetic perturbations in each species. We will integrate these metabolic profiles with expression profiles collected (in a parallel project) in our lab under the same conditions and identify functional metabolic modules of co- varying metabolites and genes in each species. We will use a novel computational approach to identify orthologous modules across species and reconstruct their evolution. The evolutionary reconstruction will predict conserved functional entities as well as major evolutionary changes in metabolic function and regulation. We will delete predicted key genes in all relevant species in our model and use the same metabolomics approach to profile their responses. The resulting profiles will validate our functional predictions and refine our evolutionary reconstruction. This innovative comparative metabolomic approach will provide insights into the function and evolution of distinct metabolic strategies and establish a new systems-level approach for the study of metabolic systems. Broad principles of metabolic evolution and regulation inferred from our analysis of yeast can be brought to bear on understanding and modeling human metabolism. The presence of two human pathogens in our study means our analysis will lead to a deeper understanding of the evolution of pathogenicity and the role of metabolism in virulence, infection, and treatment. Insights into metabolic evolution will also help to explain pathological changes in metabolism in human diseases, such as diabetes and cancer. Understanding these phenomena, includingthe respiro-fermentative growth states common to some yeasts and many cancer cells, may ultimately lead to better diagnostics and therapeutics. [unreadable] [unreadable] [unreadable]